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Generative AI has been one of the biggest technological buzzwords in 2023. Whether you’re reading a recent article or watching an interview with industry experts, everyone is talking about it. Companies are running fast to upgrade their offerings with generative AI and stay ahead of their competitors.

In the excitement of bringing new technology to your organization, don’t forget it comes with potential risks. According to a survey by Salesforce, 71% of senior IT leaders are concerned with risks introduced by generative AI. What are the most talked about generative AI risks? How can generative AI harm your organization? What steps can companies take to mitigate generative AI risks? Let’s explore.

4 generative AI risks for companies

1. Accuracy

Generative AI models learn from large amounts of data used to train them. While responding to a query, the tools generalize their data and provide answers. This means they may give inaccurate information for some specific queries. Hallucination is also one of the common generative AI risks. If you wish to verify the answers or check facts, no inherent source may be available.

2. Security and privacy

Generative AI thrives on data. The more data it gets, the better it performs. This data must be stored somewhere while the AI models learn and adapt. This means you need to keep your company’s sensitive data in third-party storage spaces. You are required to rely on third parties to secure your data. Ensure you choose a trusted third party that provides reliable assurance to mitigate generative AI risks.

Generative AI models can take some private information from the training data and reveal it unintentionally, making accidental data leaks one of the crucial generative AI risks for companies. This can be your employees’ personal information or your organization’s confidential business information. For example, while chatting with an AI chatbot, an employee inputs information about a confidential business deal. The generative AI tool stores this data indefinitely and uses the information to produce other outputs.

3. Bias

Generative AI outputs are as good as their datasets. Due to this, AI outputs may be biased. For instance, if a minor community is underrepresented in the training data, the AI model may give results misrepresenting them. The model may also increase the biases over time as it optimizes patterns and analyzes trends. Additionally, it may create content that is inappropriate for certain cultures.

4. Unintended use and unintentional disclosure

Generative AI chatbots make the power of AI available to millions of people. Human ingenuity is harnessing this capability in creative and unbounded ways. Company employees may, therefore, create new capabilities without considering important intellectual property considerations. Operational risks may emerge as interesting new capabilities are shared and grow organically across the company outside of normal training and support processes. The indiscriminate use of sensitive data may expose that information outside of privacy expectations putting customers and the company at risk.

How to mitigate generative AI risks

Organizations need to be proactive in managing AI risks. You need an actionable, reliable, and clear framework to assess AI risks and use generative AI securely. To mitigate generative AI risks, act quickly and continuously, even ahead of regulatory considerations.

Generative AI learns and adapts from data. Make sure that your data is accurate, updated, and organized. Once you automate a system, don’t forget about it. Have a human monitor it to check for biases, intentions, and correctness. Test your AI programs regularly and seek feedback from employees, customers, and key stakeholders.

Following appropriate guidelines and continuous monitoring can help you manage AI risks and keep your organization secure.

HITRUST AI Assurance Program

HITRUST launched its AI Assurance Program, the first and only system focused on achieving and sharing cybersecurity control assurances for generative AI and other emerging AI applications. Read our strategy document and stay tuned for additional blog posts. Check out our recent press release, HITRUST Releases the Industry’s First AI Assurance Program.

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